There are currently many finger image sensors available from various vendors. For example, various fingerprint sensors and systems (including fingerprint swipe sensors, fingerprint placement sensors, and fingerprint sensors of other types) are described in U.S. Pat. Nos. 6,459,804, 6,289,114, 5,177,802, 4,933,976, and 4,429,413, which patents are hereby incorporated by reference. Other fingerprint sensors, systems, and methods are described in co-pending United States patent applications assigned to Atrua Technologies, Inc. 1696 Dell Avenue, Campbell, Calif. 95008, including in U.S. patent application Ser. No. 10/099,558 entitled Fingerprint Biometric Capture Device and Method with Integrated On-Chip Data Buffering and published as U.S. 2003/0021495 A1; and U.S. patent application Ser. No. 10/134,042 entitled Capacitance Sensor System with Improved Capacitance Measuring Sensitivity and published as U.S. 2003/0016849 A1.
Regardless of the specific fingerprint sensing technology used, there are two broad categories of fingerprint sensors: placement sensors and swipe sensors. Placement sensors are large enough to image a finger (or pertinent portion of the finger containing the fingerprint) simply by placing the tip of the finger on the sensing surface and acquiring the data in a single step. Swipe sensors, on the other hand, are too small to capture an entire fingerprint image with a single sensor field of view or acquisition step. Instead, users must move (or swipe) their finger across the smaller sensor while it captures multiple frames of data, each frame containing a portion of the full or complete fingerprint image. The individual image frames are “reconstructed” into a complete fingerprint image so that they can be processed with conventional feature extraction and matching algorithms. One such method of reconstruction is given in U.S. patent application Ser. No. 10/194,994 filed 12 Jul. 2002 by inventor Anthony P. Russo and entitled Method And System For Biometric Image Assembly From Multiple Partial Biometric Frame Scans and published as U.S. 20030126448A1, which is hereby incorporated by reference. Some examples of feature extraction methods are given in references, such as for example in U.S. Pat. Nos. 6,681,034B1, U.S. Pat. No. 6,668,072B1, U.S. Pat. No. 6,480,617B2, U.S. Pat. No. 6,041,133, U.S. Pat. No. 5,613,014, U.S. Pat. No. 5,420,937, and U.S. Pat. No. 5,109,428 as well as the documents referenced in the references cited section of these patents. The result of feature extraction is called the fingerprint “template” and contains all the distilled information from the original image that is required to match that fingerprint to previously enrolled templates.
As stated above, in the current state of the art, a full or complete image of the fingerprint is typically reconstructed using a set of smaller image frames obtained from a swipe sensor type fingerprint device. However, there are reasons why creating a complete image of the fingerprint prior to the feature extraction step is undesirable.
Security is one of the most compelling reasons for not generating or storing a complete fingerprint image: if a complete fingerprint image never exists in memory or is never otherwise stored as a full image or data set, it cannot be stolen by hackers or used by others in possession of the device carrying the sensor to impersonate the person to whom the fingerprint belongs. Note that in some security systems there is a desirability to have the person physically present at the time the fingerprint image is acquired and therefore permitting a full or complete fingerprint image to be constructed, also offers an opportunity for the constructed full or complete fingerprint image or corresponding data set representing the fingerprint image to be stored and misused. Such complete fingerprint image may even occur unintentionally, such as in the event that the computing system carrying the fingerprint sensor hangs and retains a copy of the sensed fingerprint image independent of intended operation, or in the event that spy ware, or other hacker or malicious code has been introduced into the computer and attempts to detect the presence of a fingerprint image file or data set and capture it. These are only examples, and those workers in the art will appreciate that there are many other scenarios for accidental or intentional misuse of complete fingerprint images.
Swipe sensors are also more attractive than placement sensors for integration into mobile computing and communication devices such as mobile and cellular phones, personal data assistants (PDAs), and other embedded systems because they are smaller. The smaller size reduces cost as well as power consumption, both of which are more significant issues on embedded devices than on a more expensive personal computer (PC) platform. The smaller size also reduces the surface area needed to present the sensor to the user so that it can be used for other purposes and the smaller exposed area also reduces the potential for damage to the sensor.
Computing efficiency is also an important consideration for embedded devices and reduction of computation and/or computational overhead while still maintaining required security is an ever increasing need.